import os

import numpy as np
# import joblib
# from sklearn.externals import joblib
# import pickle
import lightgbm as lgb


# sk_model = joblib.load(model_path)
# pkl_file = open(model_path, 'rb')
# sk_model = pickle.load(pkl_file)
sk_model = lgb.Booster(model_file=r'C:\Users\28508\Desktop\lgbm.txt')
file_path = r'C:\Users\28508\Desktop\train_data\train\Subject_0001.npy'

data = np.load(file_path)
pre_result = sk_model.predict([data])
print()